High fidelity simulations enabled by high-performance computing will allow for unprecedented predictive power of molecular level processes that are not amenable to experimental measurement.

A poem inspired by radioactive tank waste—“Can a Scientist Dream it Alone?”—was awarded first place in the Department of Energy’s Poetry of Science Art Contest.

PNNL is honoring its postdoctoral researchers as part of the fourteenth annual National Postdoc Appreciation Week with seven profiles of postdocs from around the Laboratory.

A new review describes the insights that may be gained into important electrochemical processes using ion soft landing.

Methods review suggests ways to use artificial intelligence and machine learning to handle missing data when integrating two or more omics approaches.

Combining peptoids and carbon nanotube porins creates a new class of stable membranes with potential applications in separations science.

Gosline works to develop computational algorithms that are uniquely targeted for rare disease work by doing foundational research in model system development. This work can be expanded to all model systems in human disease.

Data-driven autonomous technology to rapidly design and deliver antiviral interventions targeting SARS-CoV-2 to reduce drug discovery timeline and advance bio preparedness capabilities.

Findings show method to better prepare human lung tissue for study; it represents the latest mass spectrometry-based omics advances.

Silicone wristbands could be more convenient option for collecting exposure data.

A new perspective article discusses how integrating carbon dioxide capture and conversion in solvents can lead to cheaper and more efficient carbon management systems.

Providing a perspective on the importance of integrating experimental work with theory and simulations when designing new carbon capture solvents.

PNNL scientists have developed a new mass spectrometry method for in-depth analysis of proteins in individual cells.

Ionic liquids bound to thin layers of graphene oxide produces more selective and efficient multi-layer membranes for water filtration.

Data from increasingly complex mass spectrometry instruments met with adaptable data analysis solution.

Surface characterization allows researchers to explore the compatibility between different solvent-membrane combinations.

Researchers characterize protein signatures that indicate Acute Kidney Injury in COVID-19 patients.

Simulations reveal advantages of using new model vs. allometric scaling for risk assessment.

A multi-institutional team has developed a deep learning framework to identify novel molecules as drug candidates.

Hypergraphs can more faithfully identify important genes in complex immune responses.